Can PDDL be utilized for action recognition?
I don't know of any work on this with respect to PDDL, but this is very similar to a conceptual dependency application called SAM (Script Applier Mechanism). Conceptual Dependency (CD) models actions using a number of primitives (which could be seen as equivalent to PDDL primitive actions):  PTRANS for physical transfer, PROPEL for application of a physical force to an object, GRASP for grasping an object, etc. Their number varies around 12 or so, depending on the version of CD.

Stories are described by a sequence of primitive acts, which have slots for actor, object, etc. They are supposed to enable a program to draw inferences about what happens. A common problem when trying to understand stories is that often common knowledge about a situation is omitted; the standard example here is going to a restaurant. It is usually assumed that the listener/reader knows what commonly happens when the protagonist enters a restaurant, so that when they leave without paying this is recognised as something unusual.

The approach used to solve this problem is to encode such knowledge in scripts, sequences of primitive acts. When triggered, eg by "Manuel went to a restaurant", this script is retrieved, and the following actions are looked for in the script. Anything that is recognised is used to fill gaps in the story, eg sitting down at a table, or looking at a menu. This was the task of the SAM program.

Basically you have a sequence of primitive actions, and you try to recognise a more abstract event "going to a restaurant" from that. Obviously you'd need to have a script to recognise, but one could presumably use this to derive a sequence of more generalised events, such as "retrieving an object from a high place", or "standing on top on another object".

The theory of using scripts, plans, and goals to describe human reasoning is detailed in Schank, Roger; Abelson, Robert P. (1977). Scripts, plans, goals and understanding: An inquiry into human knowledge structures. New Jersey: Erlbaum. ISBN 0-470-99033-3.